code: def infer_feature_range(X_train: np.ndarray) -> np.ndarray:
      """Infers the feature range from the training set.
  
      Parameters
      ----------
      X_train
          Training set.
  
      Returns
      -------
      Feature range.
      """
      X_train = X_train.reshape(X_train.shape[0], -1)
      return np.vstack((X_train.min(axis=0), X_train.max(axis=0))).T
  
file_path: alibi/alibi/confidence/model_linearity.py
imports: import logging
  import string
  from time import time
  from typing import Callable, List, Optional, Tuple, Union
  import numpy
  from numpy.linalg import norm
  from sklearn.neighbors import NearestNeighbors
label_desc: Use image node_id 7 for calling a global function with example usage: infer_feature_range(X_train) and returns: np